IMPACT OF ARTIFICIAL INTELLIGENCE ON BUSINESS EDUCATION CURRICULUM DEVELOPMENT AND MANAGEMENT IN UNIVERSITIES IN NORTH EASTERN, NIGERIA
Abstract
This study determined the impact of Artificial Intelligence (AI) on Business Education curriculum development and management in universities within North-eastern, Nigeria. The study was conducted within North eastern Nigeria. The study employed a cross-sectional research design, the population of the study comprised 149 business educators. The study employed the use of census sampling technique; hence, total population was used. Structured questionnaire was used as the instrument for data collection which was validated by experts. The reliability of the instrument obtained was 0.82. Data was analyzed using simple linear regression. The findings revealed that AI personalized learning, improved efficiency and enhanced engagement influences Business education curriculum development and management in universities. The study concludes that AI can improve educational outcomes when it is integrated, implemented and managed with efficiency, transparency and ethical considerations into the business education curriculum. It therefore, recommended that Business educators should ensure maximization of AI personalized learning and minimize its drawbacks through the development of AI literacy, further harness AI improved efficiency and potential on fairness, trust, and integrity to enhance curriculum development and improve universities students’ performance. Also, Business educators should enhance engagement on AI powered interactive content and simulations, and ensure it is designed to promote equity, inclusivity and accountability for AI-driven curriculum development and management in the university settings.
Keywords: Impact, Artificial Intelligence, Curriculum Development, Business Education
Full Text:
PDFReferences
bulibdeh, A., Zaidan, E., & Abulibdeh, R. (2024). Navigating the confluence of artificial intelligence and education for sustainable development in the era of industry 4.0: Challenges, opportunities, and ethical dimensions. Journal of Cleaner Production, 140527.
Aithal, P. S., & Maiya, A. K. (2023). Innovations in Higher Education Industry–Shaping the Future. International Journal of Case Studies in Business, IT, and Education (IJCSBE), 7 (4), 283-311.
Aymen, D. I. F., & Zakarya, B. O. (2024). The Influence of Artificial Intelligence on Students' Critical Thinking (Doctoral dissertation, university center of abdalhafid boussouf-MILA).
Barreto, A. M., & Ramalho, D. (2019). The impact of involvement on engagement with brand posts. Journal of Research in Interactive Marketing, 13 (3), 277-301.
Borenstein, J., & Howard, A. (2021). Emerging challenges in AI and the need for AI ethics education. AI and Ethics, 1, 61-65.
Bulathwela, S., Pérez-Ortiz, M., Holloway, C., Cukurova, M., & Shawe-Taylor, J. (2024). Artificial intelligence alone will not democratise education: On educational inequality, techno- solutionism and inclusive tools. Sustainability, 16 (2), 781.
Cantú-Ortiz, F. J., Galeano Sánchez, N., Garrido, L., Terashima-Marin, H., & Brena, R. F. (2020). An artificial intelligence educational strategy for the digital transformation. International Journal on Interactive Design and Manufacturing, 14, 1195-1209.
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. free Access, 8, 75264-75278.
Díaz-Rodríguez, N., Del Ser, J., Coeckelbergh, M., de Prado, M. L., Herrera-Viedma, E., & Herrera,
F. (2023). Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation. Information Fusion, 99, 101896.
Fisher, M. M., & Baird, D. E. (2020). Humanizing user experience design strategies with NEW technologies: AR, VR, MR, ZOOM, ALLY and AI to support student engagement and retention in higher education. In International perspectives on the role of technology in humanizing higher education. Emerald Publishing Limited. 105-129.
Fullan, M. (2016). The New Meaning of Educational Change. Teachers College Press.
Grafanaki, S. (2016). Autonomy challenges in the age of big data. Fordham Intell. Prop. Media & Ent. LJ, 27, 803.
Grimmelikhuijsen, S. (2023). Explaining why the computer says no: Algorithmic transparency affects the perceived trustworthiness of automated decision‐making. Public Administration Review, 83(2), 241-262.
Hargreaves, A., & Shirley, D. (2009). The fourth way. The inspiring future for educational change.
Jossey-Bass.
Igbokwe, I. C. (2023). Application of artificial intelligence (AI) in educational management. International Journal of Scientific and Research Publications, 13(3), 300- 307.
Kabudi, T., Pappas, I., & Olsen, D. H. (2021). AI-enabled adaptive learning systems: A systematic mapping of the literature. Computers and Education: Artificial Intelligence, 2, 100017.
Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M., Păun, D., & Mihoreanu, L. (2021).
Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions. Sustainability, 13(18).
Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J., Ogata, H., & Tsai, C. C. (2020). Challenges and future directions of big data and artificial intelligence in education. Frontiers in psychology, 11, 580820.
Olateju, O., Okon, S. U., Olaniyi, O. O., Samuel-Okon, A. D., & Asonze, C. U. (2024). Exploring the concept of explainable AI and developing information governance standards for enhancing trust and transparency in handling customer data. Available at SSRN. Retrieved on 30/8/24.
Oluyemisi, O. M. (2023). Impact of Artificial intelligence in Curriculum Development in Nigerian Tertiary Education. International Journal of Educational Research, 12(2), 192-211.
Omrani, N., Rivieccio, G., Fiore, U., Schiavone, F., & Agreda, S. G. (2022). To trust or not to trust? An assessment of trust in AI-based systems: Concerns, ethics and contexts. Technological Forecasting and Social Change, 181.
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development.
Rogers, E. M. (1962). Diffusion of Innovation. 1st ed. Free press.
Romiszowski, A. J. (2016). Designing instructional systems: Decision making in course planning and curriculum design. Routledge.
Sunikka, A., & Bragge, J. (2008, January). What, who and where: insights into personalization.
In Proceedings of the 41st annual Hawaii international conference on system sciences (HICSS 2008) (pp. 283-283). IEEE.
Tariq, M. U., Poulin, M., & Abonamah, A. A. (2021). Achieving operational excellence through artificial intelligence: Driving forces and barriers. Frontiers in psychology, 12, 686624.
Tomás, C., & Teixeira, A. (2020). Ethical challenges in the use of AI in education: On the path to personalization. In EDEN 2020. Online Research Workshop. European Distance and E- Learning Network (EDEN). 217-226.
Vinichenko, M. V., Melnichuk, A. V., & Karácsony, P. (2020). Technologies of improving the university efficiency by using artificial intelligence: Motivational aspect. Entrepreneurship and sustainability issues, 7(4), 2696.
Vistorte, A. O. R., Deroncele-Acosta, A., Ayala, J. L. M., Barrasa, A., López-Granero, C., & Martí- González, M. (2024). Integrating artificial intelligence to assess emotions in learning environments: a systematic literature review. Frontiers in Psychology, 15, 1387089.
Wischmeyer, T. (2020). Artificial intelligence and transparency: opening the black box. Regulating artificial intelligence, 75-101.
Zidane, Y. J. T., & Olsson, N. O. (2017). Defining project efficiency, effectiveness and efficacy. International Journal of Managing Projects in Business, 10(3), 621-641
Refbacks
- There are currently no refbacks.